Row 9675

Row ID: 9675 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 9675 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

I'm an engineer on a team working on an LLM-based support chatbot at my company. In my opinion, these types of tools are very important.

Building around LLMs presents a lot of challenges that I haven't encountered before in other types of development. The universe of inputs/outputs from an LLM is so broad that it is hard to effectively eval it independent of live interactions. Sure, you can (and should) build up some eval datasets that you can run automated evals against but they will barely scratch the surface of the range of inputs/outputs you will actually encounter so your best quality signal will come from real-time monitoring of customer interactions.

I can't speak to the usefulness or quality of any particular tool though since my company is notorious for their "not built here" mentality so we've mostly built these systems out from scratch.

FieldValue
text I'm an engineer on a team working on an LLM-based support chatbot at my company. In my opinion, these types of tools are very important. Building around LLMs presents a lot of challenges that I haven't encountered before in other types of development. The universe of inputs/outputs from an LLM is so broad that it is hard to effectively eval it independent of live interactions. Sure, you can (and should) build up some eval datasets that you can run automated evals against but they will barely sc…
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-20
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Raw Record

{
  "text": "I'm an engineer on a team working on an LLM-based support chatbot at my company. In my opinion, these types of tools are very important.\n\nBuilding around LLMs presents a lot of challenges that I haven't encountered before in other types of development. The universe of inputs/outputs from an LLM is so broad that it is hard to effectively eval it independent of live interactions. Sure, you can (and should) build up some eval datasets that you can run automated evals against but they will barely scratch the surface of the range of inputs/outputs you will actually encounter so your best quality signal will come from real-time monitoring of customer interactions.\n\nI can't speak to the usefulness or quality of any particular tool though since my company is notorious for their \"not built here\" mentality so we've mostly built these systems out from scratch.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-20",
  "username_encoded": "Z0FBQUFBQm5Lakw1MnlXYkpKN0lEN2ZvR2tlRHdOazlweEJCNmVZMTFfOXVRdXFpNFRITmcweXJOb3I5M0dBNHRIU3dVcnRxaWNYakRFQlkzRU43SFRJSUV5NkdZZGkyaE1hcE1mSHo3Vk9namJUdENRWHVtajA9",
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}
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